In the hyperiqasolver.py file, why Param. Requires_grad = False? about hyperiqa HOT 4 OPEN

Since the weight parameters of the target network are determined by the hyper network, the target network shoudn't participate the process of training.

Note that by setting 'Requires_grad = False', the target network doesn't allocate gradients during training, but it still delivers gradients to its former hyper network, which makes our model trainable.

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Since the weight parameters of the target network are determined by the hyper network, the target network shoudn't participate the process of training.

Note that by setting 'Requires_grad = False', the target network doesn't allocate gradients during training, but it still delivers gradients to its former hyper network, which makes our model trainable.

Hi @SSL92, have you tried the other way? Is the result different?

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Hi @SSL92 @huahua-c, I tested and found the the program never ran into the for loop, for param in model_target.parameters():. These two lines are indeed redundant.

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I see. Thank you very much for your answer！

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